Automatic test equipment for the measurement and analysis of complex signals as exemplified by video signals is known. Among others, the current assignee, Advanced Testing Technologies, Inc., develops such equipment including instrumentation and related software.
The capability of video test instrumentation is mainly limited to commercial standard video format frame capture coupled with basic timing and analog component analysis. Because of the complexity, verification of image content is limited to that of very basic human pattern recognition, such as vertical or horizontal bars, grayscale, checkerboards or other images with easily discernable attributes for the user/operator to analyze through visual comparison. Image content is often a critical requirement in the pass/fail criterion of a system. Testing a system's image content becomes a trade-off requiring selection between utilizing canned, standard tests that a system manufacturer would provide, a hot mockup or investment in a thorough objective analysis. The latter of which requires test development time that a user would be required to undertake to create a test for a nonstandard, specific (perhaps, proprietary) image.
Validation of video signals (as well as other electrical signals) is typically based upon synchronous and asynchronous timing measurements, analog voltage measurements and/or visual content accuracy. An analog video standard, such as RS-170, describes specific time durations and voltage amplitudes for all of its components. The number of discrete analog measurements necessary for 100% compliance to the commercial standard is in the tens of thousands. Typical compromise to verify an RS-170 signal would include duration measurements of sync pulses, blanking intervals, and line time, and comparison of one or more of these measurements to specified limits. Next, voltage amplitude tests of those components would be measured and examined in a similar fashion.
Visual image content testing is designed around the expected image. If the image consists of a series of white bars on a black background, the start and end pixel denoting the location of each bar (located by, for example, measuring pixel amplitudes) may be compared to the expected location of the bar. If the signal characteristics are less than ideal due to, for example, equipment and/or cabling anomalies, the edge of the illuminated bar may possess a slow rise or fall time, a condition that would present visually as blurry (no distinct edges). Other possible failure modes include electrical noise, intermittent glitches, and ringing (reflections). Identification of these anomalies in an automated environment requires extensive testing, is easily missed by the user/operator performing analysis or is simply ignored.
The inventors herein have identified a need to provide a means to create an adaptive method which will expediently validate perfect or imperfect video signals (or other complex electrical signals) who through analysis combine timing measurements, analog voltage measurements and ultimately image content verification. In the present art, this method is not believed to be known. The invention, described below, was created to solve this problem.
As for related prior art, U.S. Pat. No. 6,502,045, assigned to the current assignee, includes a description of an ‘error bounds tool’, and which patent is incorporated by reference herein. Differing from the error bounds tool disclosed in the '045 patent, the present invention adds a new and novel method to automatically extract complex signal characteristics to create a set of rules from a known, good (golden) video image, describing the timing relationships, analog levels and image content, apply or compare the set of rules to a video image under-test and give a statistical report of the analysis including a pass/fail determination. As will be described more fully below, the present invention is capable of reducing the test development time resulting in measurable economic and time savings. In addition, it is now possible to test images, such as actual, complex military radar imagery, that would not have been possible with current off-the-shelf commercial equipment. Historically, this level of testing required an operator-in-the-loop to manually examine such a signal. Additional savings are produced by removing manual operations from the testing sequence.